Libraries llama-cpp-python How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="AI-Engine/Phi-3-medium-4k-instruct-GGUF",
filename="Phi-3-medium-4k-instruct.BF16.gguf",
)
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
) Notebooks Google Colab Kaggle Local Apps llama.cpp How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with llama.cpp:
Install from brew brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16
# Run inference directly in the terminal:
llama-cli -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16
# Run inference directly in the terminal:
llama-cli -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Use pre-built binary # Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Build from source code git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Use Docker docker model run hf.co/AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 LM Studio Jan Ollama How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with Ollama:
ollama run hf.co/AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Unsloth Studio new How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL) curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AI-Engine/Phi-3-medium-4k-instruct-GGUF to start chatting Install Unsloth Studio (Windows) irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AI-Engine/Phi-3-medium-4k-instruct-GGUF to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AI-Engine/Phi-3-medium-4k-instruct-GGUF to start chatting Docker Model Runner How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with Docker Model Runner:
docker model run hf.co/AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Lemonade How to use AI-Engine/Phi-3-medium-4k-instruct-GGUF with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull AI-Engine/Phi-3-medium-4k-instruct-GGUF:BF16 Run and chat with the model lemonade run user.Phi-3-medium-4k-instruct-GGUF-BF16 List all available models lemonade list 
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AI-Engine/Phi-3-medium-4k-instruct-GGUF", filename="", )